System and method for providing targeted recommendations to segments of users of a virtual space

• US 8,764,561 B1
• Filed: 10/02/2012
• Issued: 07/01/2014
• Est. Priority Date: 10/02/2012
• Status: Active Grant

• Current Assignee: Kabam (Netmarble Corporation)
• Original Assignee: Kabam (Netmarble Corporation)
• Inventors: Lan, Tian, Liu, Bing, Shenoy, Sainath, Yu, Kenneth, Zhao, Liang
• Primary Examiner(s): Lewis, David L
• Assistant Examiner(s): Hoel, Matthew D
• Application Number:
  US13/633,782
• Time in Patent Office: 637 Days
• Field of Search: 463/16, 463/20, 463 11- 13, 463 17- 19, 463/25, 463 26- 28, 463 30- 32, 463 40- 42, 715/758, 715/757, 715/753, 715/751, 705/319, 725/133, 725/141, 725/153
• US Class Current: 463/31
• CPC Class Codes: A63F 13/25 Output arrangements for video game devices
• CPC Class Codes: A63F 13/5375 for graphically or textually suggesting an action, e.g. by displaying an arrow indicating a turn in a driving game
• CPC Class Codes: A63F 13/79 involving player-related data, e.g. identities, accounts, preferences or play histories
• CPC Class Codes: A63F 13/795 for finding other players; for building a team; for providing a buddy list
• CPC Class Codes: A63F 2300/556 Player lists, e.g. online players, buddy list, black list

Abstract

Targeted recommendations may be provided to specific user segments. The users may be segmented on or more user parameters that facilitate targeted provision of recommendations to the individual segments of users. A recommendation may prompt a user to take a recommended action in the game.

Claims

1. A system configured to provide recommendations to one or more users of a virtual space, the system comprising:

one or more processors configured to execute compute program modules, the computer program modules comprising;

a space module configured to execute an instance of a virtual space, and to implement the instance of the virtual space to facilitate participation by one or more users in a game within the space by determining view information from the instance and transmitting the view information to one or more client computing platforms associated with the one or more users that facilitate presentation of views of the virtual space to the one or more users by the one or more client computing platforms;

a parameter module configured to obtain respective values of user parameters for the one or more users;

a segmentation module configured to form one or more segments of the one or more users based on a value of the one or more respective user parameters;

a recommendation generation module configured to generate one or more sets of alternative recommendations for respective one or more segments of the one or more users, wherein a recommendation prompts a user to take a recommended action in the game, wherein the recommendation generation module is configured such that, responsive to the one or more segments of users including a first segment, the recommendation generation module generates at least a first set of alternative recommendations for the first segment that includes a first recommendation recommending a first recommended action and a second recommendation recommending a second recommended action that is different from the first recommended action;

a recommendation transmission module configured to transmit recommendations to the appropriate users;

a recommendation tracking module configured to track responses of the users of the first segment to the individual recommendations such that, responsive to transmission of the first recommendation to a first subset of users in the first segment and to the transmission of the second recommendation to a second subset of users in the first segment, the recommendation tracking module tracks responses of the first subset of users to the first recommendation and tracks responses of the second subset of users to the second recommendation; and

a recommendation analysis module configured to assess a relative effectiveness of recommendations transmitted to one or more segments of users based on responses of users of the one or more segments such that, responsive to the tracking of the responses of the first subset of users to the first recommendation and to the tracking of the responses of the second subset of users to the second recommendation, the recommendation analysis module determines whether the first recommendation or the second recommendation is more effective for the first segment of users.

2. The system of claim 1, wherein the segmentation module is configured to form segments of the users on one or more of a demographic parameter, a social parameter, a game parameter, or an activity parameter.

3. The system of claim 2, wherein the segmentation module is configured to form segments of the users on at least a demographic parameter, and wherein the demographic parameter includes one or more of age, sex, geographic location, language, income, education, career, or marital status.

4. The system of claim 2, wherein the segmentation module is configured to form segments of the users on at least a social parameter, and wherein the social parameter includes one or more of a parameter derived from a social graph in a social network service, an in-game relationship, or a platform from which the virtual space is accessed.

5. The system of claim 2, wherein the segmentation module is configured to form segments of the users on at least a game parameter, and wherein the game parameter includes one or more of an entity class, an entity faction, a usage amount, one or more usage times, a level, inventory in the virtual space, or a score.

6. The system of claim 2, wherein the segmentation module is configured to form segments of the users on at least an activity parameter, and wherein the activity parameter includes a parameter determined from an action history of the user in the virtual space.

7. The system of claim 1, wherein the relative effectiveness of a given recommendation is determined as a function of a number of users that perform a recommended action included in the given recommendation.

8. The system of claim 1, wherein the relative effectiveness of a given recommendation is determined as a function of retention of users that perform a recommended action included in the given recommendation versus users that do not perform the recommended action included in the given recommendation.

9. The system of claim 1, where the relative effectiveness of the first recommendation with respect to the second recommendation is determined as a function of retention of the first subset of users in the first segment relative to retention of the second subset of users in the first segment.

10. The system of claim 9, wherein retention of the first subset of users is quantified as one or more of an average retention time of users in the first subset of users, an average retention time of users in the first subset that perform the first recommended activity, a number of users in the first subset that are retained for a threshold amount of time, a number of users in the first subset that spend a threshold amount of money on the game, or an average revenue per user in the first subset.

11. The system of claim 1, wherein the relative effectiveness of the first recommendation with respect to the second recommendation is determined as a function of an average amount of participation by the first subset of users in the game within the virtual space within a given time after transmission of the first recommendation relative to an average amount of participation by the second subset of users in the game within the virtual space within the given time after transmission of the second recommendation.

12. The system of claim 1, wherein the relative effectiveness of the first recommendation with respect to the second recommendation is determined as a function of an average amount of time from the transmission of the first recommendation to the first subset to participation by the first subset of users in the game within the virtual space relative to an average amount of time from the transmission of the second recommendation to the second subset to participation by the second subset of users.

13. A computer-implemented method of providing recommendations to one or more users of a virtual space, the method being implemented in a computer system comprising one or more physical processors, the method comprising:

executing an instance of a virtual space;

implementing the instance of the virtual space to facilitate participation by the one or more users in a game within the space by determining view information from the instance and transmitting the view information to one or more client computing platforms associated with the one or more users that facilitate presentation of views of the virtual space to the one or more users by the one or more client computing platforms;

obtaining values of respective user parameters for the one or more users, the respective user parameters comprising at least a first parameter;

forming at least a first segment of users from the one or more users based on a value of the first parameter;

generating at least a first set of alternative recommendations for the first segment, wherein a recommendation prompts a user to take a recommended action in the game, the first set of recommendations including at least a first recommendation and a second recommendation, and wherein the first recommendation recommends a first recommended action and the second recommendation recommends a second recommended action that is different from the first recommended action;

transmitting the recommendations to appropriate users;

tracking responses of the users of the first segment to the individual recommendations, the tracking including, responsive to the transmission of the first recommendation to a first subset of users of the first segment and the transmission of the second recommendation to a second subset of users of the first segment, tracking the responses of one or more users of the first subset to the first recommendation and tracking the responses of one or more users of the second subset to the second recommendation; and

assessing a relative effectiveness of recommendations transmitted to the first segment based on the responses of the users of the first segment, the assessing including determining whether the first recommendation or the second recommendation is more effective for the first segment of users.

14. The method of claim 13, wherein the first parameter includes one or more of a demographic parameter, a social parameter, a game parameter, or an activity parameter.

15. The method of claim 14, wherein the first parameter includes at least a demographic parameter, and wherein the demographic parameter includes one or more of age, sex, geographic location, language, income, education, career, or marital status.

16. The method of claim 14, wherein the first parameter includes at least a social parameter, and wherein the social parameter includes one or more of a parameter derived from a social graph in a social network service, an in-game relationship, or a platform from which the virtual space is accessed.

17. The method of claim 14, wherein the first parameter includes at least a game parameter, and wherein the game parameter includes one or more of an entity class, an entity faction, a usage amount, one or more usage times, a level, inventory in the virtual space, or a score.

18. The method of claim 14, wherein the first parameter includes at least an activity parameter, and wherein the activity parameter includes a parameter determined from an action history of the user in the virtual space.

19. The method of claim 13, wherein the relative effectiveness of a given recommendation is determined as a function of the number of users that perform a recommended action included in the given recommendation.

20. The method of claim 19, wherein the relative effectiveness of a given recommendation is determined as a function of retention of users that perform a recommended action included in the given recommendation versus users that do not perform the recommended action included in the given recommendation.

21. The method of claim 20, wherein retention of the first subset of users is quantified as one or more of an average retention time of users in the first subset of users, an average retention time of users in the first subset that perform the first recommended activity, a number of users in the first subset that are retained for a threshold amount of time, a number of users in the first subset that spend a threshold amount of money on the game, or an average revenue per users in the first subset.

22. The method of claim 13, wherein the relative effectiveness of the first recommendation with respect to the second recommendation is determined as a function of an average amount of participation by the first subset of users in the game within the virtual space within a given time after transmission of the first recommendation relative to an average amount of participation by the second subset of users in the game within the virtual space within the given time after transmission of the second recommendation.

23. The method of claim 13, wherein the relative effectiveness of the first recommendation with respect to the second recommendation is determined as a function of an average amount of time from the transmission of the first recommendation to the first subset of users to participation by the first subset of users in the game within the virtual space relative to an average amount of time from the transmission of the second recommendation to the second subset of users to participation by the second subset of users.